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Advanced sensation and actuation abilities of various living organisms in nature have inspired researchers to design bioinspired self‐sensing soft actuators. However, the majority of conventional soft actuators primarily possess actuation capabilities while lacking a real‐time sensing signal feedback. Here, a promising strategy is reported to develop highly stretchable and conductive hydrogels for bioinspired self‐sensing soft actuators, which integrate actuation and strain‐sensing functions into a single materials system. The conductive hydrogels are designed and fabricated by in situ copolymerization of amino‐functionalized MXene‐encapsulated liquid metal nanodroplets (LM@A‐MXene) and poly(N‐isopropylacrylamide) hydrogels with controllable activated nanogels as nano‐cross‐linkers. The resulting hydrogel presents a compacted conducting network and highly porous microstructure, giving rise to robust integration of high conductivity, excellent strain sensitivity, broad stretchability, high stability, and fast response speed. Interestingly, the gradient network structure, formed by self‐precipitation of LM@A‐MXene, endows the hydrogel with shape‐programmable actuation, light‐driven remote control, and self‐sensing function. As a proof‐of‐concept application, the soft gripper based on the self‐sensing hydrogel actuators is developed, which can not only grasp, lift, and release objects, but also perceive every movement state by monitoring resistance changes. The proposed self‐sensing soft actuator can offer new insights for developing smart soft robotics and other artificial intelligent devices. [ABSTRACT FROM AUTHOR]

Organic cycles play an important role in chemistry, pharmacology and material science for their unique properties. Construction of organic cycles from thioalkynes attracted increasing attention due to the facile access of thioalkynes. 2H‐Azirines were synthesized successfully from thioalkynyl oxime ethers. Cyclobutanes were formed through chiral titanium catalyzed cycloaddition of thioalkynes. Cyclopentenes were afforded by annulation of thioalkynes. Thioalkynes could be also applied to synthesize thiophenes, oxazoles, benzo[b]thiophenes, 2H‐chromenes, 2‐phenylbenzothiazoles, diazacyclobutene, etc. In this review, construction of organic cycles from thioalkynes were highlighted. Firstly, the property and application of organic cyclic compounds were simply introduced. After presenting the general methods to access organic cycles, applications of thioalkynes as synthons to prepare organic cycles were classified and presented in detail. Based on different kinds of organic cycles obtained from thioalkynes, organic reactions for synthesis of three‐, four‐, five‐, six‐membered as well as fused cycles would be summarized and the plausible reaction mechanisms could be presented if available. [ABSTRACT FROM AUTHOR]

Sulfur‐containing alkynes, are important starting materials and intermediates in organic reactions. Some of sulfur‐containing alkynes display interesting bioactivities and are potentially applied as drugs. Various synthetic methodologies towards sulfur‐containing alkynes have been developed, including C(sp)−S coupling, thiolation, S‐alkynylation, trifluoromethylthiolation, etc. In this review, the approaches towards alkynyl sulfides in recent 3 years, as well as to form alkynyl trifluoromethyl sulfides and alkynylthiocyanates were highlighted. Firstly, the property and application of alkynes were introduced. After presenting the superiority of sulfur‐containing alkynes, their synthetic methods were classified and presented in details. According to different kinds of sulfur‐containing alkynes, synthetic methodologies for alkynyl sulfides, alkynyl trifluoromethyl sulfides and alkynylthiocyanates were summarized and the proposed reaction mechanisms were demonstrated if available. [ABSTRACT FROM AUTHOR]

Sophisticated sensing and actuation capabilities of many living organisms in nature have inspired scientists to develop biomimetic somatosensory soft robots. Herein, the design and fabrication of homogeneous and highly conductive hydrogels for bioinspired somatosensory soft actuators are reported. The conductive hydrogels are synthesized by in situ copolymerization of conductive surface‐functionalized MXene/Poly(3,4‐ethylenedioxythiophene)/poly(styrenesulfonate) ink with thermoresponsive poly(N‐isopropylacrylamide) hydrogels. The resulting hydrogels are found to exhibit high conductivity (11.76 S m−1), strain sensitivity (GF of 9.93), broad working strain range (≈560% strain), and high stability after over 300 loading–unloading cycles at 100% strain. Importantly, shape‐programmable somatosensory hydrogel actuators with rapid response, light‐driven remote control, and self‐sensing capability are developed by chemically integrating the conductive hydrogels with a structurally colored polymer. As the proof‐of‐concept illustration, structurally colored hydrogel actuators are applied for devising light‐driven programmable shape‐morphing of an artificial octopus, an artificial fish, and a soft gripper that can simultaneously monitor their own motions via real‐time resistance variation. This work is expected to offer new insights into the design of advanced somatosensory materials with self‐sensing and actuation capabilities, and pave an avenue for the development of soft‐matter‐based self‐regulatory intelligence via built‐in feedback control that is of paramount significance for intelligent soft robotics and automated machines. [ABSTRACT FROM AUTHOR]

With the growth of high performance electronics, more consideration should be given to the safety issues associated with thermal runaway. Previous strategies have often been limited by shutdown efficiency and shutdown temperature. Here, we present a MXene supercapacitor loaded with a smart thermally responsive electrolyte to cope with thermal runaway at high temperatures. At room temperature, the ions in the electrolyte containing the poly (N‐isopropylacrylamide‐co‐glycidyl methacrylate) (PNGM) can migrate freely and the devices can operate normally. The smart electrolyte system forms a hydrophobic network that effectively inhibits ion migration to achieve thermal shutdown at high temperatures. The electrolyte system exhibits different electrochemical properties during heating up, reaching nearly 90 % capacity suppression at 85 °C. The proposed smart electrolyte system provides a promising solution to the thermal safety suitable for current electronic devices by achieving a proactive protection strategy. [ABSTRACT FROM AUTHOR]

Flexible artificial intelligence and rechargeable electronic devices have been the research hotpot due to the status quo of the energy crisis. However, the existing energy storage devices suffering from undesirable electrochemical performance, poor flexibility, and toxicity, have unsatisfactory practical application prospect. Owing to its unique stability, normal electrodes in energy storage equipment are built out of carbon‐based materials. Recently, zinc hybrid supercapacitors have attracted a lot of attention. Herein, a high‐performance zinc‐ion hybrid micro‐supercapacitor is successfully constructed using hierarchical honeymoon‐like porous carbon frameworks as cathode by direct ink printing method. Due to the bivalent feature of zinc and electric double layered capacitive characteristic of the porous carbon, the optimized device possesses excellent electrochemical performance of excellent specific capacity of 189.06 mA h g−1 at a current density of 1 mA cm−2, high energy density of76.38 Wh kg−1, power density of 499.94 W kg−1 and superior capacity retention of 95.71 % at 10 mA cm−2 after 1000 cycles. Through direct ink printing, the as‐assembled zinc hybrid micro‐supercapacitors based on flexible substrate exhibit outstanding flexibility with controllable active material mass loading. [ABSTRACT FROM AUTHOR]

Purpose: Coronavirus disease 2019 (COVID‐19) has caused a serious global health crisis. It has been proven that the deep learning method has great potential to assist doctors in diagnosing COVID‐19 by automatically segmenting the lesions in computed tomography (CT) slices. However, there are still several challenges restricting the application of these methods, including high variation in lesion characteristics and low contrast between lesion areas and healthy tissues. Moreover, the lack of high‐quality labeled samples and large number of patients lead to the urgency to develop a high accuracy model, which performs well not only under supervision but also with semi‐supervised methods. Methods: We propose a content‐aware lung infection segmentation deep residual network (content‐aware residual UNet (CARes‐UNet)) to segment the lesion areas of COVID‐19 from the chest CT slices. In our CARes‐UNet, the residual connection was used in the convolutional block, which alleviated the degradation problem during the training. Then, the content‐aware upsampling modules were introduced to improve the performance of the model while reducing the computation cost. Moreover, to achieve faster convergence, an advanced optimizer named Ranger was utilized to update the model's parameters during training. Finally, we employed a semi‐supervised segmentation framework to deal with the problem of lacking pixel‐level labeled data. Results: We evaluated our approach using three public datasets with multiple metrics and compared its performance to several models. Our method outperforms other models in multiple indicators, for instance in terms of Dice coefficient on COVID‐SemiSeg Dataset, CARes‐UNet got the score 0.731, and semi‐CARes‐UNet further boosted it to 0.776. More ablation studies were done and validated the effectiveness of each key component of our proposed model. Conclusions: Compared with the existing neural network methods applied to the COVID‐19 lesion segmentation tasks, our CARes‐UNet can gain more accurate segmentation results, and semi‐CARes‐UNet can further improve it using semi‐supervised learning methods while presenting a possible way to solve the problem of lack of high‐quality annotated samples. Our CARes‐UNet and semi‐CARes‐UNet can be used in artificial intelligence‐empowered computer‐aided diagnosis system to improve diagnostic accuracy in this ongoing COVID‐19 pandemic. [ABSTRACT FROM AUTHOR]

Severe mechanical ocular trauma with no light perception (NLP) predicts a poor prognosis of visual acuity and enucleation of the eyeball. Since the innovative treatment concept of exploratory vitreoretinal surgery has developed and treatment technology has advanced, the outcomes of severe ocular trauma treatment in NLP patients have greatly improved. However, there remains a lack of unified standards for the determination, surgical indication, and timing of vitrectomy in NLP eye treatment. To address these problems, we aimed to create evidence-based medical guidelines for the diagnosis, treatment, and prognosis of mechanical ocular trauma with NLP. Sixteen relevant recommendations for mechanical ocular trauma with NLP were obtained, and a consensus was reached. Each recommendation was explained in detail to guide the treatment of mechanical ocular trauma associated with NLP., (© 2022 The Authors. Journal of Evidence-Based Medicine published by Chinese Cochrane Center, West China Hospital of Sichuan University and John Wiley & Sons Australia, Ltd.)